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  • Open Access

    ARTICLE

    Hybrid Algorithm-Driven Smart Logistics Optimization in IoT-Based Cyber-Physical Systems

    Abdulwahab Ali Almazroi1,*, Nasir Ayub2

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3921-3942, 2023, DOI:10.32604/cmc.2023.046602 - 26 December 2023

    Abstract Effectively managing complex logistics data is essential for development sustainability and growth, especially in optimizing distribution routes. This article addresses the limitations of current logistics path optimization methods, such as inefficiencies and high operational costs. To overcome these drawbacks, we introduce the Hybrid Firefly-Spotted Hyena Optimization (HFSHO) algorithm, a novel approach that combines the rapid exploration and global search abilities of the Firefly Algorithm (FO) with the localized search and region-exploitation skills of the Spotted Hyena Optimization Algorithm (SHO). HFSHO aims to improve logistics path optimization and reduce operational costs. The algorithm’s effectiveness is systematically… More >

  • Open Access

    ARTICLE

    Whale Optimization Algorithm-Based Deep Learning Model for Driver Identification in Intelligent Transport Systems

    Yuzhou Li*, Chuanxia Sun, Yinglei Hu

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3497-3515, 2023, DOI:10.32604/cmc.2023.035878 - 31 March 2023

    Abstract Driver identification in intelligent transport systems has immense demand, considering the safety and convenience of traveling in a vehicle. The rapid growth of driver assistance systems (DAS) and driver identification system propels the need for understanding the root causes of automobile accidents. Also, in the case of insurance, it is necessary to track the number of drivers who commonly drive a car in terms of insurance pricing. It is observed that drivers with frequent records of paying “fines” are compelled to pay higher insurance payments than drivers without any penalty records. Thus driver identification act… More >

  • Open Access

    ARTICLE

    Intelligent Vehicular Communication Using Vulnerability Scoring Based Routing Protocol

    M. Ramya Devi*, I. Jasmine Selvakumari Jeya

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 31-45, 2023, DOI:10.32604/iasc.2023.026152 - 06 June 2022

    Abstract Internet of Vehicles (IoV) is an intelligent vehicular technology that allows vehicles to communicate with each other via internet. Communications and the Internet of Things (IoT) enable cutting-edge technologies including such self-driving cars. In the existing systems, there is a maximum communication delay while transmitting the messages. The proposed system uses hybrid Co-operative, Vehicular Communication Management Framework called CAMINO (CA). Further it uses, energy efficient fast message routing protocol with Common Vulnerability Scoring System (CVSS) methodology for improving the communication delay, throughput. It improves security while transmitting the messages through networks. In this research, we… More >

  • Open Access

    ARTICLE

    Vehicle Positioning Based on Optical Camera Communication in V2I Environments

    Pankaj Singh1, Huijin Jeon2, Sookeun Yun2, Byung Wook Kim3, Sung-Yoon Jung1,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2927-2945, 2022, DOI:10.32604/cmc.2022.024180 - 29 March 2022

    Abstract Demand for precise vehicle positioning (VP) increases as autonomous vehicles have recently been drawing attention. This paper proposes a scheme for positioning vehicles on the move based on optical camera communication (OCC) technology in the vehicle-to-infrastructure (V2I) environment. Light-emitting diode (LED) streetlights and vehicle cameras are used as transmitters and receivers respectively. Regions of streetlights are detected and traced by examining images that are obtained from cameras of vehicles. Then, a scheme for analyzing visible light data extracted from the images is proposed. The proposed vehicle positioning scheme uses information on angles between vectors that… More >

  • Open Access

    ARTICLE

    A Particle Swarm Optimization Based Deep Learning Model for Vehicle Classification

    Adi Alhudhaif1,*, Ammar Saeed2, Talha Imran2, Muhammad Kamran3, Ahmed S. Alghamdi3, Ahmed O. Aseeri1, Shtwai Alsubai1

    Computer Systems Science and Engineering, Vol.40, No.1, pp. 223-235, 2022, DOI:10.32604/csse.2022.018430 - 26 August 2021

    Abstract Image classification is a core field in the research area of image processing and computer vision in which vehicle classification is a critical domain. The purpose of vehicle categorization is to formulate a compact system to assist in real-world problems and applications such as security, traffic analysis, and self-driving and autonomous vehicles. The recent revolution in the field of machine learning and artificial intelligence has provided an immense amount of support for image processing related problems and has overtaken the conventional, and handcrafted means of solving image analysis problems. In this paper, a combination of… More >

  • Open Access

    ARTICLE

    Internet of Things Based Solutions for Transport Network Vulnerability Assessment in Intelligent Transportation Systems

    Weiwei Liu1, Yang Tang2, Fei Yang2, Chennan Zhang1, Dun Cao3, Gwang-jun Kim4, *

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2511-2527, 2020, DOI:10.32604/cmc.2020.09113 - 16 September 2020

    Abstract Intelligent Transportation System (ITS) is essential for effective identification of vulnerable units in the transport network and its stable operation. Also, it is necessary to establish an urban transport network vulnerability assessment model with solutions based on Internet of Things (IoT). Previous research on vulnerability has no congestion effect on the peak time of urban road network. The cascading failure of links or nodes is presented by IoT monitoring system, which can collect data from a wireless sensor network in the transport environment. The IoT monitoring system collects wireless data via Vehicle-to-Infrastructure (V2I) channels to… More >

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